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The Buyer’s Guide to AI Usage Control. Today’s “AI everywhere” reality is woven into everyday workflows across the enterprise, embedded in SaaS platforms, browsers, copilots, extensions, and a rapidly expanding universe of shadow tools that appear faster than security teams can track. Yet most organizations still rely on legacy controls that operate far away from where AI interactions actually occur. The result is a widening governance gap where AI usage grows exponentially, but visibility and control do not.  With AI becoming central to productivity, enterprises face a new challenge: enabling the business to innovate while maintaining governance, compliance, and security.  A new Buyer’s Guide for AI Usage Control argues that enterprises have fundamentally misunderstood where AI risk lives. Discovering AI Usage and Eliminating ‘Shadow’ AI will also be discussed in an upcoming virtual lunch and learn.  The surprising truth is that AI security isn’t a data problem or an app problem. It’s an interaction problem. And legacy tools aren’t built for it. AI Everywhere, Visibility Nowhere If you ask a typical security leader how many AI tools their workforce uses, you’ll get an answer. Ask how they know, and the room goes quiet. The guide surfaces an uncomfortable truth: AI adoption has outpaced AI security visibility and control by years, not months. AI is embedded in SaaS platforms, productivity suites, email clients, CRMs, browsers, extensions, and even in employee side projects. Users jump between corporate and personal AI identities, often in the same session. Agentic workflows chain actions across multiple tools without clear attribution. And yet the average enterprise has no reliable inventory of AI usage, let alone control over how prompts, uploads, identities, and automated actions are flowing across the environment. This isn’t a tooling issue, it’s an architectural one. Traditional security controls don’t operate at the point where AI interactions actually occur. This gap is exactly why AI Usage Control has emerged as a new category built specifically to govern real-time AI behavior. AI Usage Control Lets You Govern AI Interactions AUC is not an enhancement to traditional security but a fundamentally different layer of governance at the point of AI interaction. Effective AUC requires both discovery and enforcement at the moment of interaction, powered by contextual risk signals, not static allowlists or network flows. In short, AUC doesn’t just answer “What data left the AI tool?” It answers “Who is using AI? How? Through what tool? In what session? With what identity? Under what conditions? And what happened next?” This shift from tool-centric control to interaction-centric governance is where the security industry needs to catch up. Why Most AI “Controls” Aren’t Really Controls Security teams consistently fall into the same traps when trying to secure AI usage: Each of these creates a dangerously incomplete security posture. The industry has been trying to retrofit old controls onto an entirely new interaction model and it simply doesn’t work.  AUC exists because no legacy tool was built for this. AI Usage Control Is More Than Just Visibility In AI usage control, visibility is only the first checkpoint not the destination. Knowing where AI is being used matters, but the real differentiation lies in how a solution understands, governs, and controls AI interactions at the moment they happen. Security leaders typically move through four stages:  Technical Considerations: Guide the Head, But Ease of Use Drives the Heart While technical fit is paramount, non-technical factors often decide whether an AI security solution succeeds or fails: These considerations are less about "checklists" and more about sustainability, ensuring the solution can scale with both organizational adoption and the broader AI landscape. The Future: Interaction-centric Governance Is the New Security Frontier AI isn’t going away, and security teams need to evolve from perimeter control to interaction-centric governance.  The Buyer’s Guide for AI Usage Control offers a practical, vendor-agnostic framework for evaluating this emerging category. For CISOs, security architects, and technical practitioners, it lays out: AI Usage Control isn’t just a new category; it’s the next phase of secure AI adoption. It reframes the problem from data loss prevention to usage governance, aligning security with business productivity and enterprise risk frameworks. Enterprises that master AI usage governance will unlock the full potential of AI with confidence. Download the Buyer’s Guide for AI Usage Control to explore the criteria, capabilities, and evaluation frameworks that will define secure AI adoption in 2026 and beyond.